Unravelling Anti-Predator Strategies in African Savannas through a UAV-based Approach

Predation is a fundamental ecological process that shapes the behaviour and survival strategies of prey species. In my PhD research, I use a novel combination of experimentally induced disturbances, drone technology, and computer vision to unravel the complexities of anti-predator behaviour in African mammalian herbivores. My research employs drone-based videography to track the behaviour of plains zebra and impala under various simulated predator threat scenarios. Computer vision algorithms will be employed to automatically identify, track, and record individual movements, enabling the quantification of behavioural parameters and the analyses of consistent among-individual variation in movement characteristics. The PhD research will address four key objectives: 1) differentiating between responses to human- and non-human predator disturbances, 2) examining the influence of environmental factors such as visual complexity and habitat heterogeneity on anti-predator behaviour, 3) exploring the impact of social context including group size and composition on anti-predator behaviour, and 4) quantifying individual differences in spatial behaviour and consistency thereof. This research will integrate theoretical frameworks from predator-prey interactions and movement ecology to guide the experimental design and data analysis. The proposed methods not only advance our understanding of anti-predator behaviour but also offer a promising tool for wildlife monitoring and conservation.